1.2k citations · 8.7k across the 141 of their papers we have counts for
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Deep Visual-Semantic Alignments for Generating Image Descriptions
Andrej Karpathy, Li Fei-Fei
We present a model that generates natural language descriptions of images and their regions. Our approach leverages datasets of images and their sentence descriptions to learn abou…
Affordances Provide a Fundamental Categorization Principle for Visual Scenes
Michelle R. Greene, Christopher Baldassano, Andre Esteva +2
How do we know that a kitchen is a kitchen by looking? Relatively little is known about how we conceptualize and categorize different visual environments. Traditional models of vis…
Visual Noise from Natural Scene Statistics Reveals Human Scene Category Representations
Michelle R. Greene, Abraham P. Botros, Diane M. Beck +1
Our perceptions are guided both by the bottom-up information entering our eyes, as well as our top-down expectations of what we will see. Although bottom-up visual processing has b…
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky, Jia Deng, Hao Su +9
The ImageNet Large Scale Visual Recognition Challenge is a benchmark in object category classification and detection on hundreds of object categories and millions of images. The ch…
VideoSET: Video Summary Evaluation through Text
Serena Yeung, Alireza Fathi, Li Fei-Fei
In this paper we present VideoSET, a method for Video Summary Evaluation through Text that can evaluate how well a video summary is able to retain the semantic information containe…
Deep Fragment Embeddings for Bidirectional Image Sentence Mapping
Andrej Karpathy, Armand Joulin, Li Fei-Fei
We introduce a model for bidirectional retrieval of images and sentences through a multi-modal embedding of visual and natural language data. Unlike previous models that directly m…